Last week, the AI nonprofit METR published an in-depth study on human-AI collaboration that stunned experts. It found that software developers with access to AI tools took 19% longer to complete their tasks, despite believing they had finished 20% faster. The findings shed important light on our ability to predict how AI capabilities interact with human skills.

Since 2020, we have been conducting similar studies on human-AI collaboration, but in contexts with much higher stakes than software development. Alarmingly, in these safety-critical settings, we found that access to AI tools can cause humans to perform much, much worse.

A 19% slowdown in software development can eat into profits. Reduced performance in safety-critical settings can cost lives.

Safety-Critical Scenarios

Imagine that you’re aboard a passenger jet on its final approach into San Francisco. Everything seems ready for a smooth landing — until an AI-infused weather monitor misses a sudden microburst. [...]

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Outline:

(01:04) Safety-Critical Scenarios

(03:30) How Current Safety Frameworks Fail

(05:43) AI Influences Humans to Perform Slightly Better... or Much, Much Worse

(08:50) A Clear Pattern in Human-AI Collaboration

(09:49) Three Rules for Better Evaluations

(11:43) Faster, Easier, and Earlier Evaluations

(13:48) Toward Responsible Deployments of AI

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Narrated by TYPE III AUDIO.

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